Autofocusing Method Based on Dynamic Modulation Transfer Function Feedback

Accurate measurement of key optical system parameters (such as focal length, distortion, and modulation transfer function (MTF)) depends critically on obtaining sharp images. Conventional autofocus methods are susceptible to noise in complex imaging environments, prone to convergence to local optima, and often exhibit low efficiency. To address these limitations, this paper proposes a high-precision autofocus method based on dynamic MTF feedback. The method employs frequency-domain MTF as a real-time image sharpness metric, enhancing robustness in noisy conditions. For the search mechanism, particle swarm optimization (PSO) is combined with the golden-section search to establish a hybrid optimization framework of “global coarse localization–local fine search,” balancing convergence speed and focusing accuracy. Experimental results show that the proposed method achieves stable and efficient autofocus, providing reliable imaging assurance for high-precision measurement of optical system parameters and demonstrating strong engineering applicability.